Characterization of the Immune Cell Infiltration Landscape Uncovers Prognostic and Immunogenic Characteristics in Lung Adenocarcinoma - Wang, Xin; Xu, Zhenyi; Liu, Zhilin; Lin, Weihao; Cao, Zheng; Feng, Xiaoli; Gao, Yibo; He, Jie (Frontiers in Genetics, 2022)
The immune cell infiltration in TME has been reported associated with prognosis and immunotherapy efficiency of lung cancers. However, to date, the immune infiltrative landscape of lung adenocarcinoma (LUAD) has not yet been elucidated. Therefore, this study was aimed to identify a new transcriptomic-based TME classification and develop a risk scoring system to predict the clinical outcomes of patients with LUAD. Herein, we applied ‘CIBERSORT’ algorithm to analyze the transcriptomic data of LUAD samples and classified the LUAD into four discrete subtypes according to the distinct immune cell infiltration patterns. Furthermore, we established a novel predictive tool (TMEscore) to quantify the immune infiltration patterns for each LUAD patient by principal component analysis. The TMEscore displayed as a reliable and independent prognostic biomarker for LUAD, with worse survival in TMEscrore-high patients and better survival in TMEscrore-low patients and in both TCGA and other 5 GEO cohorts. In addition, enriched pathways and genomic alterations were also analysed and compared in different TMEsocre subgroups, and we observed that high TMEscore was significantly correlated with more aggressive molecular changes, meanwhile low TMEscore subgroup enriched in immune active related pathways. The TMEscore-low subtype showed overexpression of PD-1, CTLA4 and associations of other markers of sensitivity to immunotherapy, including TMB, immunophenoscore (IPS) analysis and tumor immune dysfunction and exclusion (TIDE) algorithm. Conclusively, TMEscore is a promising and reliable biomarker to distinguish the prognosis, the molecular and immune characteristics, and the benefit from ICIs treatments in LUAD.